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- ItemSimulation of atmospheric organic aerosol using its volatility-oxygen-content distribution during the PEGASOS 2012 campaign(Katlenburg-Lindau : EGU, 2018) Karnezi, Eleni; Murphy, Benjamin N.; Poulain, Laurent; Herrmann, Hartmut; Wiedensohler, Alfred; Rubach, Florian; Kiendler-Scharr, Astrid; Mentel, Thomas F.; Pandis, Spyros N.A lot of effort has been made to understand and constrain the atmospheric aging of the organic aerosol (OA). Different parameterizations of the organic aerosol formation and evolution in the two-dimensional volatility basis set (2D-VBS) framework are evaluated using ground and airborne measurements collected in the 2012 Pan-European Gas AeroSOls-climate interaction Study (PEGASOS) field campaign in the Po Valley (Italy). A number of chemical aging schemes are examined, taking into account various functionalization and fragmentation pathways for biogenic and anthropogenic OA components. Model predictions and measurements, both at the ground and aloft, indicate a relatively oxidized OA with little average diurnal variation. Total OA concentration and O: C ratios are reproduced within experimental error by a number of chemical aging schemes. Anthropogenic secondary OA (SOA) is predicted to contribute 15-25% of the total OA, while SOA from intermediate volatility compound oxidation contributes another 20-35%. Biogenic SOA (bSOA) contributions varied from 15 to 45% depending on the modeling scheme. Primary OA contributed around 5% for all schemes and was comparable to the hydrocarbon-like OA (HOA) concentrations derived from the positive matrix factorization of the aerosol mass spectrometer (PMF-AMS) ground measurements. The average OA and O: C diurnal variation and their vertical profiles showed a surprisingly modest sensitivity to the assumed vaporization enthalpy for all aging schemes. This can be explained by the interplay between the partitioning of the semi-volatile compounds and their gas-phase chemical aging reactions.
- ItemStatus and future of numerical atmospheric aerosol prediction with a focus on data requirements(Katlenburg-Lindau : EGU, 2018) Benedetti, Angela; Reid, Jeffrey S.; Knippertz, Peter; Marsham, John H.; Di Giuseppe, Francesca; Rémy, Samuel; Basart, Sara; Boucher, Olivier; Brooks, Ian M.; Menut, Laurent; Mona, Lucia; Laj, Paolo; Pappalardo, Gelsomina; Wiedensohler, Alfred; Baklanov, Alexander; Brooks, Malcolm; Colarco, Peter R.; Cuevas, Emilio; da Silva, Arlindo; Escribano, Jeronimo; Flemming, Johannes; Huneeus, Nicolas; Jorba, Oriol; Kazadzis, Stelios; Kinne, Stefan; Popp, Thomas; Quinn, Patricia K.; Sekiyama, Thomas T.; Tanaka, Taichu; Terradellas, EnricNumerical prediction of aerosol particle properties has become an important activity at many research and operational weather centers. This development is due to growing interest from a diverse set of stakeholders, such as air quality regulatory bodies, aviation and military authorities, solar energy plant managers, climate services providers, and health professionals. Owing to the complexity of atmospheric aerosol processes and their sensitivity to the underlying meteorological conditions, the prediction of aerosol particle concentrations and properties in the numerical weather prediction (NWP) framework faces a number of challenges. The modeling of numerous aerosol-related parameters increases computational expense. Errors in aerosol prediction concern all processes involved in the aerosol life cycle including (a) errors on the source terms (for both anthropogenic and natural emissions), (b) errors directly dependent on the meteorology (e.g., mixing, transport, scavenging by precipitation), and (c) errors related to aerosol chemistry (e.g., nucleation, gas-aerosol partitioning, chemical transformation and growth, hygroscopicity). Finally, there are fundamental uncertainties and significant processing overhead in the diverse observations used for verification and assimilation within these systems. Indeed, a significant component of aerosol forecast development consists in streamlining aerosol-related observations and reducing the most important errors through model development and data assimilation. Aerosol particle observations from satellite- and ground-based platforms have been crucial to guide model development of the recent years and have been made more readily available for model evaluation and assimilation. However, for the sustainability of the aerosol particle prediction activities around the globe, it is crucial that quality aerosol observations continue to be made available from different platforms (space, near surface, and aircraft) and freely shared. This paper reviews current requirements for aerosol observations in the context of the operational activities carried out at various global and regional centers. While some of the requirements are equally applicable to aerosol-climate, the focus here is on global operational prediction of aerosol properties such as mass concentrations and optical parameters. It is also recognized that the term "requirements" is loosely used here given the diversity in global aerosol observing systems and that utilized data are typically not from operational sources. Most operational models are based on bulk schemes that do not predict the size distribution of the aerosol particles. Others are based on a mix of "bin" and bulk schemes with limited capability of simulating the size information. However the next generation of aerosol operational models will output both mass and number density concentration to provide a more complete description of the aerosol population. A brief overview of the state of the art is provided with an introduction on the importance of aerosol prediction activities. The criteria on which the requirements for aerosol observations are based are also outlined. Assimilation and evaluation aspects are discussed from the perspective of the user requirements.